(for admission click or visit http://admission.gtu.ac.in/)
Vision
To prepare the data, information and knowledge professionals in the field of data science in order to meet the needs of the global information society.
Mission
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To provide the in-depth understanding of the key technologies of data science to the learners.
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To develop the state-of-art laboratory facilities with well-equipped academic infrastructure.
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To encourage the faculty members for consultancy projects in the field of data science.
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To establish strong linkages with data science companies and institutes having national importance.
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To promote the innovative practices in order to produce innovators and entrepreneurs in the field of data science.
Brief about PG Diploma in Data Science
By use of various web-based and mobile-based applications, voluminous data is generated. Hence, it becomes challenging task to handle these data and most importantly to understand the data. Looking at the current and futuristic trends, there will be demand of data science experts who can understand the nature of data, analyze the data and take result-oriented decisions after analysis of the data. This program is for students who are interested in developing skills in data science and data analytics.
During one year of program the students will learn insights of subjects like Machine Learning, Programming in Python, Blockchain Technology, Big Data Analytics, Data Analysis using R, Cloud Computing etc.
After acquiring the skills from this program, the candidates can be employed as
(1) Data Engineer who is responsible for creating the infrastructure for collating data from various sources, cleaning it, transforming it and storing it so that it can be used by other people in the team.
(2) Data Scientist whose work typically starts where the job of data engineer ends. He is responsible for extracting insights from the data using various tools & techniques, producing basic data visualizations and reporting dashboards
(3) Machine Learning Engineer who is responsible for analyzing data using data preparation and cleaning techniques, statistical/predictive analytics techniques and interpreting the statistical output (hypothesis testing, ANOVA, regression (linear, logistic), clustering, time series, decision trees, naive bayes and many more), machine learning techniques, etc.
Duration Tuition Fee Intake
1 year (2 semesters) Rs.12,500 per semester 30 students
Eligibility
Recognized bachelor degree in any branch of engineering OR
Recognized bachelor degree in science stream with mathematics subject OR
Recognized degree in Master of Computer Application (MCA) OR
Recognized degree in M.Sc. (IT)
Major Focused Subjects
- Machine Learning
- Programming in Python
- Blockchain Technology
- Big Data Analytics
- Data Analysis using R
- Cloud Computing
Job Opportunities
A role of Data Analyst/Engineer in small/large scale or MNC company depending on the skills acquired during the program.
Salient Features of Program
- Run by PG School of State Government University.
- Run in GTU-Chandkheda campus conveniently reachable from any part of city/state.
- Guided by senior academicians and industry experts in capacity of advisors.
- Frequent Expert Sessions conducted by various industry experts.
- Hostel facility is available with-in campus.
Frequently Asked Questions
ESE (E) = University Theory Exam (External)
ESE (V) = University Practical Exam (Viva)
PA (M) = Progression Assessment (Mid Semester Exam)
PA (I) = Progression Assessment (Internal Continuous Evaluation -Practical/Term Work)
Subject code and Category | Subject Name | Semester | Theory Hours | Practical Hours | Credit | ESE (E) Marks | ESE (V) Marks | PA (M) Marks | PA (I) Marks | Total Marks |
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1618001 Compulsory | Data Structures and Algorithm | 1 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1618002 Compulsory | Statistics and Exploratory Data Analysis | 1 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1618003 Compulsory | Fundamentals of Machine Learning | 1 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1618004 Compulsory | Introduction to Python Programming | 1 | 2 | 6 | 5 | 50 | 70 | 30 | 0 | 150 |
1628001 Compulsory | Software Tools for Data Management | 2 | 0 | 6 | 3 | 0 | 70 | 0 | 30 | 100 |
1628002 Compulsory | Cloud Computing | 2 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1628003 Compulsory | Big Data Analytics | 2 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1628004 Compulsory | Mini Project | 2 | 0 | 4 | 2 | 0 | 70 | 0 | 30 | 100 |
1628005 Elective | Blockchain Technology | 2 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1628006 Elective | Deep Learning | 2 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1628007 Elective | Natural Language Processing | 2 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
1628008 Elective | Business Analytics | 2 | 4 | 2 | 5 | 70 | 50 | 30 | 0 | 150 |
Tokyo
Tokyo is the capital of Japan.